The CCANED-CIPHER Study: Early Cancer Detection and Treatment Response Monitoring Using AI-Based Platelet and Immune Cell Transcriptomic Profiling

Summary

The purpose of the CCANED-CIPHER study is to develop and validate an AI-based blood test for early cancer detection and to monitor treatment effectiveness in cancer patients. This two-phase, multi-center observational study aims to identify specific transcriptomic biomarkers in platelets and immune cells that distinguish cancer patients from healthy individuals and correlate with treatment outcomes. By analysing blood samples using artificial intelligence, the study seeks to create a safe, non-invasive method to enhance cancer diagnosis and monitor treatment responses over time.

Conditions

• Brest Cancer
• Lung Cancer (NSCLC)
• Pancreatic Cancer, Adult
• Prostate Cancers
• Ovarian Cancer
• Colorectal Cancer
• Glioblastoma (GBM)
• Liver Carcinoma

Interventions

DIAGNOSTIC_TEST

DiNanoQ: A multi-cancer early detection (MCED) blood test

Procedure: Participants will undergo a single blood draw at baseline. Sample Analysis: Platelet Isolation: Platelets will be extracted from the collected blood samples. RNA Analysis: RNA from the isolated platelets will be extracted and analyzed using AI-based transcriptomic profiling to identify biomarkers associated with cancer.

OTHER

DiNanoTrack: Therapeutic Response Monitoring Blood Test

Procedures: Blood Sample Collection: Participants will have blood samples drawn at three time points: Baseline: Before therapy initiation. 6 Weeks Post-Therapy Initiation: To monitor early treatment response. 6 Months Post-Therapy Initiation: To assess longer-term therapeutic outcomes. Sample Analysis: Platelet and Immune Cell Isolation: Platelets: Extracted from each blood sample to continue monitoring RNA profiles. Immune Cells: Separated from the blood samples to analyse immune response to therapy. RNA Analysis: Platelet RNA: Analysed to observe changes in transcriptomic profiles over time using AI-based tools. Immune Cell RNA: Examined to assess transcriptomic changes associated with therapeutic responses. Data Correlation: Therapeutic Response Assessment: RNA profiles from platelets and immune cells will be correlated with clinical outcomes to identify biomarkers predictive of treatment efficacy, progression-free survival, relapse, and drug resistance.

Sponsors & Collaborators

• Javier Toledo

  lead INDUSTRY

Principal Investigators

• Solomon Rotimi, PhD · Dysplasia Diagnostics Limited

• Javier Toledo, Medical Degree · Dysplasia Diagnostics Limited

Eligibility

Min Age

40 Years

Max Age

75 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2025-12-20

Primary Completion

2027-08-01

Completion

2028-08-01

Countries

• Argentina
• Nigeria
• United Kingdom

Study Locations